docs: def treat(self):
          """adapt self.evaluations depending on the current measurement value
          and return ``sigma_fac in (1.0, self.alphasigma)``
  
          """
          if self.noiseS > 0:
              self.evaluations = min((self.evaluations * self.alphaevals, self.maxevals))
              return self.alphasigma
          else:
              self.evaluations = max((self.evaluations * self.alphaevalsdown, self.minevals))
              return 1.0